Building Mentorships for Manufacturing of the Future

Summary

The need for mentorship in manufacturing is huge. In a recent survey of 700+ global manufacturers, 91% noted they are concerned about the growing manufacturing knowledge gap due to retiring industry veterans.

It’s clear the industry faces a perfect storm of experience loss as tenured employees near retirement, massive change in how manufacturing can be done with the advent of new technologies and increased demand for skilled workers due to government investment in manufacturing across the world. Mentorship in all forms, whether traditional or new, can help shorten the time for the next generation of workers to become proficient in these roles and transform how all workers are able to leverage new technologies and work processes to remain competitive and relevant in a changing macro environment. And as the pool of ‘seasoned veterans’ gets shallower over time, more structured mentorship will be essential to replace what naturally happened on the plant floor.
 
As the manufacturing industry evolves, so too is manufacturing mentorship. The beauty today is that mentoring can take more forms than ever. While people-to-people mentoring is still the foundation or traditional form of mentorship, new AI-driven solutions can actually harness massive amounts of ‘experience’ and provide recommendations and insights that shorten the time to learn for new employees. The AI co-pilot model will increasingly become a new form of ‘mentor’ that can look over the shoulder of reliability, process and supply chain teams and provide context and insight that’s hard for any one person to master independently.
 

Mentorship gets a refresh

Most manufacturing organizations do not have a formal, built-out mentorship program. They typically leave it up to the individuals to engage with each other and tap into their networks for training and knowledge sharing. Part of that may be due to an antiquated view of mentorship where people felt burdened by the need to coach without guidance. However, real-time coaching and mentorship is actually a great use case for AI solutions to support traditional mentoring. Applications already exist for AI co-pilots that can help individuals working in maintenance and reliability, and even in process control. These co-pilots can go a long way in benefiting overall process health.
 
In recent years, we have evolved beyond the traditional, only human-led mentoring – or imparting the deep experiences of one person, which can embrace everything from job skills to career planning and emotional maturity. These touchpoints tend to be monthly or weekly sessions to reflect on the past time period. In fact, while we are seeing a brain drain in manufacturing due to aging and retirements, many of those people would be ideal mentors, given the right structures and programs.
 
Today, AI-driven feedback and insight, gathered from across the industry or multiple industries, add great depth to the learning process. AI co-pilots can provide real-time understanding and feedback to complement human coaching. These approaches together form the evolved mentorship model for the next era of manufacturing, and it will be a really powerful toolset to enable the next generation of manufacturing workforce to succeed and thrive.
 

Benefits of evolved mentorship

Establishing or revamping a mentorship program requires a lot of time and effort, and it’s often an added responsibility to an already busy team or individual. However, the benefits of an evolved mentorship program to meet today’s industry needs cannot be overlooked.
 
Notably, the biggest benefits of mentorship include the rapid transfer of experience and context – it can take years for a technician or manager to gain that via their own experiences. Transferring knowledge more rapidly helps industrial companies become more productive; it also reduces turnover, and the less experienced workers gain confidence and capabilities more quickly. Mentorship is also a great way to get a ‘cross-pollination’ of ideas and skills. The workforce in manufacturing does not traditionally change companies or roles as frequently as other industries, such as technology, so people taking the time to mentor outside of their own company or role is a great way to keep ideas fresh and raise the skill level of the entire industry.
 

Start here: Best practices for mentorship of the future

Establishing a culture conducive to mentorship is essential to the success of any program. It cannot be seen as ‘interruptive’ to getting work done. Leaders and team managers can model this expectation and build time into people’s roles both to be mentors and to receive insight as mentees. This framework can mitigate hesitation around participating in knowledge-sharing programs.
 
Instead of throwing workers into the unknown, industrial organizations should provide training and tools, both for mentors and mentees. Nobody magically becomes an expert on the do’s and don’ts of coaching and mentoring. Companies should provide tools, discussion forums and other avenues to help mentors succeed and teach mentees how to get the most value out of the process. This may look like providing guidance on how to prepare, what to expect to learn and how to engage and provide feedback.
 
Lastly, feedback and success stories are important to rounding out a mentorship program. Mentors should be recognized and celebrated for their commitment to the program. It is also helpful to source clear feedback on both the overall program and individual participants to help people improve and grow for the future of manufacturing.
 

Final thoughts

Mentorships have the potential to mitigate some of the manufacturing industry’s greatest challenges: an aging workforce and a smaller talent pool, government investment generating greater demand for talent and ongoing geopolitical turmoil speeding up nearshoring/onshoring.
 
Whether manufacturers have a defined mentorship program or have barely made a dent in establishing a semblance of such an initiative, now is the time to take action by marrying traditional models with AI-powered co-pilots. Manufacturing can only be more efficient and resilient if we combine our greatest resources to train the next generation of workers.